\begin{tabular}{p{.45\textwidth}*{4}{r@{}l}}
\hline
\hline
& \multicolumn{2}{c}{Model 1} & \multicolumn{2}{c}{Model 2}  \\
\hline
treated             &      -2.046&***&      -2.518&***&      -2.097&***&      -2.525&** \\
                    &     (0.692)&   &     (0.912)&   &     (0.704)&   &     (1.005)&   \\
v04b                &      -0.080&   &      -0.086&   &      -0.076&   &      -0.079&   \\
                    &     (0.059)&   &     (0.081)&   &     (0.060)&   &     (0.077)&   \\
population          &       0.001&*  &       0.001&   &       0.001&   &       0.001&*  \\
                    &     (0.000)&   &     (0.000)&   &     (0.000)&   &     (0.000)&   \\
v106                &      -0.001&   &      -0.003&   &      -0.006&   &      -0.009&   \\
                    &     (0.017)&   &     (0.021)&   &     (0.016)&   &     (0.019)&   \\
male                &      -0.225&   &      -0.325&   &      -0.052&   &      -0.094&   \\
                    &     (0.347)&   &     (0.521)&   &     (0.391)&   &     (0.503)&   \\
riskloss            &      -0.150&   &      -0.227&   &      -0.152&   &      -0.235&   \\
                    &     (0.135)&   &     (0.210)&   &     (0.137)&   &     (0.206)&   \\
muslim              &       1.109&*  &       1.688&*  &       0.998&*  &       1.554&*  \\
                    &     (0.638)&   &     (0.942)&   &     (0.535)&   &     (0.833)&   \\
christian           &       0.308&   &       0.615&   &       0.242&   &       0.563&   \\
                    &     (0.533)&   &     (0.761)&   &     (0.551)&   &     (0.753)&   \\
education           &            &   &            &   &      -0.130&   &      -0.192&   \\
                    &            &   &            &   &     (0.178)&   &     (0.221)&   \\
income10k           &            &   &            &   &      -0.118&   &      -0.172&   \\
                    &            &   &            &   &     (0.089)&   &     (0.162)&   \\
v205                &            &   &            &   &       0.057&   &       0.157&   \\
                    &            &   &            &   &     (0.346)&   &     (0.428)&   \\
Constant               &       3.903&***&       3.643&** &       4.351&***&       4.174&***\\
                    &     (1.148)&   &     (1.458)&   &     (1.079)&   &     (1.397)&   \\
var(e.DictatorTakeManna)&            &   &       7.193&***&            &   &       6.951&***\\
                    &            &   &     (1.459)&   &            &   &     (1.420)&   \\
\hline
N.obs.              &         127&   &         127&   &         126&   &         126&   \\
\hline \multicolumn{9}{p{\textwidth}} {\footnotesize{\textbf{Notes:} Dependent variable: coins appropriated by the dictator. Models 1 and 3: OLS regression, models 2 and 4: left-censored Tobit regression. All models include village fixed-effects. Robust standard errors clustered at the village level. Compared to models 1 and 2, models 3 and 4 controls for income, finance, and education levels. Controls include: age,  gender, religion, estimation of risk preferences. Symbols $***$, $**$, and $*$ indicate significance at the 1\%, 5\% and 10\% level, respectively.}} \end{tabular}
